meeting-analyzer

Analyze meeting transcripts for communication patterns and behavioral insights.

Updated May 28, 2026

Search Tags:#transcript analysis #meeting analysis #behavioral patterns #communication insights #coaching feedback

Ready to run

npx skills add https://github.com/SensLiao/Claude-code-setting --skill meeting-analyzer-sensliao

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: meeting-analyzer
Source: https://github.com/SensLiao/Claude-code-setting/tree/main/skills/meeting-analyzer
Command: npx skills add https://github.com/SensLiao/Claude-code-setting --skill meeting-analyzer-sensliao

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires nltk, spacy, pattern, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides deep analysis of meeting transcripts, identifying communication patterns, anti-patterns, and offering coaching feedback to improve meeting dynamics.

Core Features & Use Cases

Transcript Analysis: Analyze meeting transcripts for behavioral patterns, communication issues, and actionable feedback.
Use Case: When a user uploads a meeting transcript and wants to understand their communication style, identify areas for improvement, or compare communication across time periods.

Quick Start

Analyze the meeting transcript from the last week and provide feedback on communication patterns.

Frequently Asked Questions about meeting-analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I analyze meeting transcripts for communication patterns and behavioral insights?▼

Meeting transcript analysis identifies communication patterns, behavioral insights, and actionable feedback by detecting speaker labels, anti-patterns, and verbal habits. It processes text using pattern recognition to evaluate meeting dynamics and highlight areas for coaching improvement.

Can I use Python libraries like spacy and nltk to detect communication anti-patterns in transcripts?▼

Yes, transcript analysis uses Python libraries like spacy, nltk, and pattern for text processing and pattern recognition. These dependencies enable the extraction of verbal habits and behavioral insights by parsing natural language structures within the transcript formats.

What's the best way to get coaching feedback from meeting transcripts?▼

The best way to get coaching feedback is to analyze meeting transcripts for behavioral patterns and communication issues. The evaluation identifies specific anti-patterns and verbal habits, generating actionable feedback to improve your communication style and overall meeting dynamics.

How do I identify speaker labels when analyzing transcript formats?▼

Transcript analysis automatically identifies speaker labels to distinguish individual contributions during processing. By parsing various transcript formats, the system isolates each speaker's dialogue to accurately map communication patterns and detect specific behavioral anti-patterns per participant.

Does meeting analysis handle various transcript formats for comparing communication across time periods?▼

Meeting analysis handles various transcript formats to compare communication across time periods. By processing multiple transcripts, it tracks behavioral patterns and verbal habits chronologically, providing insights into how communication styles evolve and highlighting areas for continuous coaching feedback.

Why do I need pattern recognition libraries for behavioral pattern analysis?▼

Pattern recognition libraries are required for behavioral pattern analysis to parse natural language and identify complex verbal habits. Text processing frameworks extract the linguistic features needed to detect communication anti-patterns and generate accurate, actionable coaching feedback from raw dialogue.